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EuroBioForum 2012 | 18 April 2012Presentation by Marian Hajduch, Coordinator at BIOMEDREG
Citation preview
Introduction to Personalized Medicine in the Czech Republic and BIOMEDREG Project as a New Research
Platform for Molecular and Translational Medicine
Marian Hajduch, MD, PhD Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University in Olomouc Czech Republic EuroBioForum 2012, Brussels
• Established in 1573 •The second oldest university after the Charles Universty in Prague •Olomouc Archibishop – center of Moravian religion and education – alumni or region associated scientists: Johann Gregor Mendel, Sigmund Freund, Konrad Zirm, Otto Wichterle, Frantisek Santavy, Jiri Bartek •Currently 23.000 students, approx. 7% of Czech university students and 3000 employees
Palacký University in Olomouc
OLOMOUC
Johann Gregor Mendel
Konrad Zirm
• Part I – Introduction to
Personalized Medicine in the
Czech Republic
• Part II – BIOMEDREG Project as a
New Research Platform for Molecular
and Translational Medicine
Biomarker use
Prognostic provides information about
patient outcome,
regardless of therapy
Predictive estimates the response
to a specific treatment
before the advance
of therapy
Pharmacological
estimates changes
after treatment
associated
with target hit
by therapy
Surrogate substitutes
a clinical endpoint
History of Personalized Medicine in the Czech Republic
(Oncology)
• Started in 2002 with introduction of trastuzumab (Herceptin) on the
Czech market
•Critical role of health insurance companies (request for centralized
diagnostics of HER-2 gene)
• 2002-2010 Reference Laboratory at Palacky University in Olomouc
•2005- Systemic collection of clinical information on patients treated
with biological therapies for evaluation of cost effectiveness (drug
registries)
•2008- Introduction of six new laboratories of predictive medicine across
the country for predictive cancer biomarkers
Predictive Cancer Biomarkers – Where we are?
Mutation present
Resistant to TK
inhibitros
Cellular proliferation
and survival
Gefitini
b
Erlotini
b
EG
F
GTP k-
Ras
Raf
Mek
MAPK
PI13
AKT
Part of the clinical routine#
• Her-2 in breast and gastric cancers (trastuzumab, lapatinib)
• KRAS/BRAF mutations – colorectal cancers (cetuximab, panitumumab)
• EGFR1 mutations – NSCLC (gefitinib, erlotinib)
• BRAF mutations – melanoma (vemurafenib)*
• ALK translocations – NSCLC (crizotinib)*
#diagnostics is paid from the health insurance
*not reimbursed yet
IHC:0
FISH: normal
IHC: 1+ to 2+
IHC: 3+
FISH: amplification
CEP 17
Her-2/neu
Specialized Molecular Diagnostics of
Cancers – HER-2 gene
Laboratory/Institute holds
accreditation decision according to
CSN ISO/IEC 17025/15189 to meet
European diagnostic standards
(www.cia.cz)
Immunohistochemistry discordances among RL a LLs >1 or
>2 IHC grades
Discordance
RL vs. LLs
0-6
months
(%)
6-12
months
(%)
12-18
months
(%)
18-24
months
(%)
24-30
months
(%)
30-35
months
(%)
0-35
months
(%)
≥ 2 IHC
14,08
19,51
12,59
19,33
31,52
36,99
21,33
≥ 1 IHC
28,17
43,90
37,04
40,34
50,00
53,42
41,61
Survival analysis (TTP) of mBRC Her-2
patients on trastuzumab based therapies.
Comparison of patients examined versus
not examined in the Reference laboratory
(RL).
Median TTP of RL examined pts.: RL 64,6
weeks
Median TTP of RL not examined pts: 37,7
weeks
Overall median TTP: 48,41 weeks
PD CR+PR_SDí
0 20 40 60 80 100 120 140 160 180 200
weeks
0 %
20 %
40 %
60 %
80 %
100 %
Perc
en
tag
e o
f patie
nts
not examined in RL
examined in RL
all pts. p=0.02
N = 42 N = 83
0%
20%
40%
60%
80%
100%
RL yes RL no
Pe
rce
nta
ge
of
pa
tien
ts
CR+PR+SD
PD
Therapeutic response of metastatic Her-2
positive breast cancer patients to
trastuzumab based therapies. Comparison
of patients examined versus not examined
in the Reference laboratory (RL).
(χ2 = 6,27, df = 1, p = 0,01)
Evaluation of HER-2 gene in breast cancer patients by FISH assay in Reference laboratory in Olomouc
32 68
285 287 274
350
785
726 742
679
610
0
100
200
300
400
500
600
700
800
900
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
nu
mb
er
of
pa
tien
ts
years
trastuzumab in local BRC
trastuzumab in metastatic BRC
Ústí n. L. Masaryk Hospital
in Usti nad Labem
Liberec Regional
Hospital Liberec
České Budějovice
Regional Hospital Ceske
Budejovice
University Hospital in
Motol
University Hospital Na
Bulovce and General
University Hospital
Prague
Plzeň
Hradec
Králové
University Hospital
Hradec Kralove i
Jihlava Regional Hospital Jihlava
Olomouc
Masaryk Memorial Cancer
Institute Brno
University Hospital Brno
and St. Anne's University
Hospital
Brno
University
Hospital Olomouc
Zlín Regional
Hospital
Zlin
Nový Jičín
Regional
Hospital
Novy Jicin
University Hospital
Ostrava
Ostrava
University
Hospital Plzen
Comprehensive oncology
centers
Hematooncology centers
Predicitive medicine
laboratories
Bioinformatics, biostatistics
and drug registries
Major Comprehensive Cancer Centers and
Diagnostic Laboratories – Self Learning System
Laboratories must hold accreditation decision according to CSN ISO/IEC 17025/15189 to meet
European diagnostic standards and perform external quality control.
Forum of Oncologists
Biannual Therapeutic Standards
Sample size in the registries: overview
(the system started with Herceptin in 2005)
Breast Registry
Herceptin – adjuvant
therapy 1852
Herceptin – mBC 1120
Herceptin – combined 194
Lapatinib 222
Avastin 85
NSCLC Registry
Tarceva 2183
Alimta 819
Avastin 59
Iressa 31
Alimta - MPM 124
Tarceva – Pancreatic cancer 58
Renis – mRCC Registry
Sutent 1221
Nexavar 719
Afinitor 204
Torisel 47
Avastin 40
Registry Corect – Colorectal Cancer
Avastin 3731
Erbitux 815
Vectibix 183
TOTAL:
> 13 500 valid records
Accessible follow-up (in months)
Registry Therapy Sample Median Min Max
Breast
Herceptin – adjuvancy 1593 17,5 0,0 63,9
Herceptin - mBRC 1005 18,5 0,1 112,8
Lapatinib 213 7,8 0,0 45,3
Avastin 83 11,2 0,7 38,2
Corect
Avastin 3612 11,9 0,0 70,4
Erbitux 787 9,0 0,0 68,3
Vectibix 168 6,7 0,0 29,5
Tulung –
NSCLC
Tarceva 2121 4,3 0,0 54,3
Alimta 786 5,6 0,0 43,0
Avastin 56 7,4 0,2 18,5
Iressa 28 3,3 0,0 14,6
0 20 40 60 80 100 120
Her-adjuvance
HER-mBC
lapatinib
avastin
Avastin-crc
erbitux
vectibix
Tarceva
Alimta
Avastin
Iress
Follow-up (months)
Median Max Min Follow-up (months)
Registry Therapy Sample Median 10% 90%
Breast
Herceptin – adjuvancy1) 1132 50,9 30,0 54,6
Herceptin – mBRC1) 727 45,6 11,0 124,1
Lapatinib 149 20,6 5,7 58,4
Avastin 55 25,0 6,0 55,0
Corect
Avastin 2610 26,0 7,8 66,4
Erbitux 612 19,1 2,1 52,1
Vectibix 119 16,9 4,0 46,0
Tulung –
NSCLC
Tarceva 1671 11,0 3,0 43,9
Alimta 683 9,0 3,0 18,4
Avastin 41 16,0 3,3 29,3
Iressa 13 9,0 4,1 31,7
0 25 50 75 100 125
Herceptin - adjuvance
Herceptin - mBC
Lapatinib
Avastin - Prs
Avastin - crc
erbitux
vectibix
tarceva
alimta
avastin
iressa
Duration of applied target therapy as example of quantitative
outcome (suitable for assessment of economic demands)
Median 90% percentile 10% percentile Therapy duration (weeks)
Therapy duration (weeks)
0 12 24 36 48 60 72 84 96
0,0
0,2
0,4
0,6
0,8
1,0
Herceptin (adj. therapy) – progression-free survival
PFS % patients
(95% IC)
1yr PFS 96,9 (96,0; 97,9)
2yr PFS 94,3 (92,9; 95,7)
5yr PFS 93,4 (91,7; 95,1)
PFS
Median PFS
(95% IS) Not reached
N*=1583 Survival time calculated since the therapy onset.
Time (months)
0 12 24 36 48 60 72 84 96 108 120
0,0
0,2
0,4
0,6
0,8
1,0
PFS % patients
(95% IC)
1yr PFS 56,5 (53,3; 59,8)
2yr PFS 27,4 (24,0; 30,8)
5yr PFS 17,6 (13,9; 21,3)
PFS
Median PFS
(95% IS) 14,5 months
(12,8; 16,2)
N= 1005
Herceptin (mBRC) – progression-free survival
Survival time calculated since the therapy onset.
Time (months)
Uniqueness of the Czech National Cancer Registry
• the Czech National Cancer Registry
(CNCR) contains almost 1.8 mil. records
on cancer patients since 1977
• population-based data, covering 100% of
the Czech population
• double control of mortality data: records
are independently verified against Death
Records Database
• mortality coding according to WHO
nomenclature
• all cancer diagnoses included
Predictive information system for cancer care: Step 2 = Predictive estimation of incidence and prevalence
INCIDENCE
2012
Number of cases
(90% confidence interval)
Stage I 3,353 (3,126; 3,580)
Stage II 2,212 (2,026; 2,399)
Stage III 1,004 (884; 1,123)
Stage IV 573 (498; 649)
Unstaged 214 (157; 269)
TOTAL 7,356 (6,691; 8,020)
PREVALENCE
2012
Number of cases
(90% confidence interval)
Stage I 30,933 (30,644; 31,222)
Stage II 28,131 (27,855; 28,407)
Stage III 7,490 (7,348; 7,632)
Stage IV 3,600 (3,501; 3,699)
Unstaged 2,228 (2,150; 2,306)
TOTAL 72,382 (71,498; 73,266)
Breast cancer (C50)
Success of the breast cancer screening program: (c) increasing proportion of early-stage cancers
there has been substantial increase in proportion of
early-stage cancers during recent years
0%
20%
40%
60%
80%
100%
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Pro
port
ion o
f ca
se
s
Rok
Stage IV * DCO, cases diagnosed by autopsy, early
deaths, therapy had not been started due to
objective reasons
Unstaged
incomplete records
objective reasons*
Organised breast
cancer screening
Stage III
Stage II
Stage I Source of data:
Czech National Cancer Registry
Prof. Ladislav Dusek, Ph.D.
director
Institute of Biostatistics and Analyses
Masaryk University, Brno, Czech Republic
Jan Mužík, Ph.D., senior data analyst
Institute of Biostatistics and Analyses
Masaryk University, Brno, Czech
Republic
Data collection, mining, analysis
Conclusions
Personalized medicine (oncology) in the Czech Republic was centralized into
Comprehensive Cancer Centers and six „reference“ laboratories of predicitive
medicine.
The Czech Society for Oncology developed and implemented the full set of
registries monitoring segment of targeted anti-tumor therapy including
biomarkers.
The registries are able to collect representative multidimensional data which
cannot be obtained directly from the other sources.
Combination with other information sources allows to assess accessibility of care
and to predict incidence and prevalence of treated patients.
Registries offer comprehensive outcomes suitable for cost-effectiveness
analyses: direct and indirect care, hospital stays, dosage of medication and time
of medication, etc.
Registries offer reliable outcomes necessary for the evaluation of safety, efficacy
and quality of the care: adverse events, therapeutic response, survival,
biomarkers.
• Part I – Introduction to Personalized
Medicine in the Czech Republic
• Part II – BIOMEDREG Project as a
New Research Platform for
Molecular and Translational
Medicine
Infrastructural project for chemical biology and translational
medicine (BIOMEDREG) – concentrating, evaluating and
developing the national chemical and biomarker knowledge
Palacký University Olomouc
Biobanking
Compound
storage/library High throughput
screening
Data collection for
national &
international
databases Biomarkers
Clinical
trials
Therapeutic
standards
Universtiy Hospital Olomouc
Institute of Organic Chemistry and Biochemistry, ASCR
Institute of Chemical Technologies Prague
Preclinical
studies
Medicinal chemistry
Biomedicine for regional development and human resources
BIOMEDREG
Project Leader:
Palacký Universty in Olomouci
Partners:
University Hospital in Olomouc
Institute of Organic Chemistry and Biochemistry AS
CR
Institute of Chemical Technologies in Prague
Allocation:
Approx. 40 M €
EU Structural Funds -
2nd Priority Axis OP VaVpI
Phase of the Project:
Realization phase started on April 1, 2010
Information:
www.biomedreg.eu, www.imtm.cz
OLOMOUC
Primary aim:
To establish the Institute of
Molecular and Translational
Medicine at Palacky
University in Olomouc
Building of research infrastrucutres in the Czech Republic
2010-2012
Professor of Pathology R. Kodousek
1952-56
2012
(construction phase – 15 months,
4700 m2)
1956
Core facilities
• Genomics (HTS qPCR in 1536 format), Affymetrix platform, NGS, mass
spectrometry (Sequenome)
• Proteomics (2x MALDI-TOF/TOF, HPLC-MS, qTRAP, qTOF, orbitrap)
• Metabolomics (GC-TOF, qTRAP, orbitrap)
• Microscopy: AFM, Raman microscopy, IR microscopy, confocal spinning
disc and laser scanning microscopy, superresolution, PALM, SIM, TIRF,
transmission and raster EM)
• HTS/HCA analysis (compound library+dispensing, 3-arm robotic system for
screening of small molecules in BSL2+/BSL3 and/or hypoxic environment,
readers: fluorescence, luminisence, radioactivity, absorbance, wide field
confocal HCA, mass spectrometry based screening)
• BSL3 laboratories
• Small animal imaging centre: optical (fluorescence, luminiscence)., X-ray,
PET/CPECT/CT, ultrasound
• Radiochemistry, medicinal and combinatiorial chemistry
• Biobank
Research programs
1.Molecular basis of diseases and molecular
targets
2.Medicinal chemistry
3.Chemical biology nad experimental therapeutics
4.Biomarkers
5.Pharmacology and toxicology
6.Translational medicine
Selected outcomes of the project (since April 2010)
Publications with IF total: 96, cummulative IF=440, average IF=4,8 (IF<3: 45, IF 3-5: 27; IF
5-10: 14; IF>10: 6)
Patents: 6 national, 6 international, 1 spin-off
9 graduated PhD. students
83 scientists/PhD. students
IMTM is the national node for EATRIS: Relationship to other ESFRI and interest in
further collaborations
•BBMRI – interface: tissue and bio-banks, expertise in human and animal (model) pathology, quality standards, policies, patient data banks, disease-specific data banks;
• ECRIN – interface: transfer of projects that successfully passed clinical phase 0, I and IIa studies to progress with late phase II and beyond; use of ECRIN where multi-centre studies are needed even for early phase clinical trials; exchange observations from the clinic back to scientists (reverse translation), expertise in regulatory affairs, common training courses; • INFRAFRONTIER – interface: consultation in choosing the right animal model for pre-clinical studies, characterisation of novel and disease-specific (mouse) models; archiving of such; quality standards and regulatory standards (animal husbandry, animal studies, etc.), training courses; • INSTRUCT – interface: service in /access to specialty infrastructure components in structural biology, e.g. in small molecule characterization, elaboration of a biological mechanism of action; • EU-Openscreen – interface: collaborative use of technology and interdisciplinary expertise for small molecule discovery and development, access to large compound libraries or chemoinformatics, databases; • EuroBioImaging – interface: collaboration on nonstandard/sophisticated problems in biomolecular or biomedical imaging, training possibilities; • ELIXIR (bioinformatics and databases) – interface: exchange on IT management, standard definitions for data collection, storage, utilisation, and on a mid- to long-term basis, agreements on data hosting etc.
OLOMOUC
BRNO
BIOMEDREG EATRIS
CEITEC INSTRUCT ICRC ECRIN RECAMO BBMR
PERSONALIZED MEDICINE THE RIGHT THERAPY TO THE RIGHT PATIENT ON RIGHT
TIME LEADING TO OPTIMIZATION OF RISK/BENEFIT RATIO FOR INDIVIDUAL PATIENT
Translational Medicine Personalized Medicine
THANK YOU FOR ATTENTION
[email protected] [email protected] www.imtm.cz www.medchembio.cz